Method and apparatus for video coding

ABSTRACT

Aspects of the disclosure provide methods, apparatuses, and non-transitory computer-readable storage mediums for video encoding/decoding. An apparatus includes processing circuitry that partitions a current block of a current picture based on a geometric partitioning mode (GPM). The current block is partitioned into two partitions in the GPM mode. Each of the partitions is associated with a respective predictor. A weighting index for a sample of the current block is determined based on a position of the sample. A weighting factor is calculated based on the weighting index of the sample according to an equation that converts the weighting index to the weighting factor. The sample is encoded based on the weighting factor and the predictor corresponding to the sample.

INCORPORATION BY REFERENCE

This present application is a continuation of U.S. patent applicationSer. No. 17/063,149, “METHOD AND APPARATUS FOR VIDEO CODING,” filed onOct. 5, 2020, which claims the benefit of priority to U.S. ProvisionalApplication No. 62/953,457, “SIMPLIFICATION FOR GEO INTER BLOCK,” filedon Dec. 24, 2019, and U.S. Provisional Application No. 62/955,825,“LOOK-UP TABLE FREE METHOD IN WEIGHTING INDEX TO WEIGHT CONVERSION FORGEO INTER BLOCK,” filed on Dec. 31, 2019. The disclosures of the priorapplications are incorporated by reference herein in their entirety.

TECHNICAL FIELD

The present disclosure describes embodiments generally related to videocoding.

BACKGROUND

The background description provided herein is for the purpose ofgenerally presenting the context of the disclosure. Work of thepresently named inventors, to the extent the work is described in thisbackground section, as well as aspects of the description that may nototherwise qualify as prior art at the time of filing, are neitherexpressly nor impliedly admitted as prior art against the presentdisclosure.

Video coding and decoding can be performed using inter-pictureprediction with motion compensation. Uncompressed digital video caninclude a series of pictures, each picture having a spatial dimensionof, for example, 1920×1080 luminance samples and associated chrominancesamples. The series of pictures can have a fixed or variable picturerate (informally also known as frame rate) of, for example, 60 picturesper second or 60 Hz. Uncompressed video has significant bitraterequirements. For example, 1080p60 4:2:0 video at 8 bit per sample(1920×1080 luminance sample resolution at 60 Hz frame rate) requiresclose to 1.5 Gbit/s bandwidth. An hour of such video requires more than600 GBytes of storage space.

One purpose of video coding and decoding can be the reduction ofredundancy in the input video signal, through compression. Compressioncan help reduce the aforementioned bandwidth or storage spacerequirements, in some cases by two orders of magnitude or more. Bothlossless and lossy compression, as well as a combination thereof can beemployed. Lossless compression refers to techniques where an exact copyof the original signal can be reconstructed from the compressed originalsignal. When using lossy compression, the reconstructed signal may notbe identical to the original signal, but the distortion between originaland reconstructed signals is small enough to make the reconstructedsignal useful for the intended application. In the case of video, lossycompression is widely employed. The amount of distortion tolerateddepends on the application; for example, users of certain consumerstreaming applications may tolerate higher distortion than users oftelevision distribution applications. The compression ratio achievablecan reflect that: higher allowable/tolerable distortion can yield highercompression ratios.

A video encoder and decoder can utilize techniques from several broadcategories, including, for example, motion compensation, transform,quantization, and entropy coding.

Video codec technologies can include techniques known as interprediction. For each inter-predicted coding unit (CU), motion parametersinclude motion vectors, reference picture indices and reference picturelist usage index, and additional information to be used forinter-predicted sample generation. The motion parameters can be signaledin an explicit or implicit manner. When a CU is coded with skip mode,the CU is associated with one prediction unit (PU) and has nosignificant residual coefficients, no coded motion vector delta orreference picture index. A merge mode is specified whereby the motionparameters for a current CU are obtained from neighboring CUs, includingspatial and temporal candidates, and additional schedules introduced,for example in VVC. The merge mode can be applied to any inter-predictedCU, not only for skip mode. The alternative to merge mode is theexplicit transmission of the motion parameters. Motion vector,corresponding reference picture index for each reference picture listand reference picture list usage flag and other needed information aresignaled explicitly per each CU.

Some inter prediction coding tools include extended merge prediction,merge mode with motion vector difference (MMVD), advanced motion vectorprediction mode (AMVP) with symmetric motion vector difference (MVD)signaling, affine motion compensated prediction, subblock-based temporalmotion vector prediction (SbTMVP), adaptive motion vector resolution(AMVR), motion field storage ( 1/16th luma sample MV storage and 8×8motion field compression), bi-prediction with weighted averaging (BWA),bi-directional optical flow (BDOF), decoder side motion vectorrefinement (DMVR), triangular partitioning mode (TPM), and combinedinter and intra prediction (CIIP).

In some cases, a merge candidate list is constructed by including thefollowing five types of candidates in order: (1) spatial MVP fromspatial neighbor CUs; (2) temporal MVP from collocated CUs; (3)history-based MVP from an FIFO table; (4) pairwise average MVP; and (5)zero MVs.

The size of the merge list is signaled in a slice header and the maximumallowed size of the merge list is for example 6 in some cases. For eachCU code in merge mode, an index of the best merge candidate is encodedusing truncated unary binarization (TU). The first bin of the mergeindex is coded with context and bypass coding is used for other bins.

FIG. 1A shows exemplary positions of spatial merge candidates. In somecases, up to four merge candidates can be selected among candidateslocated in the positions depicted in FIG. 1A. The selection order is B1,A1, B0, A0, and B2. The candidate at position B2 is considered only whenany CU at positions A0, B0, B1, or A1 is not available (e.g., the CU atposition A0 belongs to another slice or tile) or not inter coded. Afterthe candidate at position A1 is added to the merge candidate list, theaddition of the remaining candidates is subject to a redundancy checkthat ensures that candidates with same motion information are excludedfrom the merge candidate list so that coding efficiency is improved.

FIG. 1B shows candidate pairs considered for the redundancy check of thespatial merge candidates. To reduce computational complexity, not allpossible candidate pairs are considered in the redundancy check.Instead, only the pairs linked with an arrow in FIG. 1B are consideredand a candidate is only added to the merge candidate list if thecorresponding candidate used for the redundancy check has not the samemotion information.

FIG. 1C shows a motion vector scaling for a temporal merge candidate. Insome cases, only one temporal merge candidate can be added to the mergecandidate list. Particularly, in the derivation of this temporal mergecandidate, a scaled motion vector is derived based on a co-located CUbelonging to the collocated reference picture. The reference picturelist used for the derivation of the co-located CU is explicitly signaledin the slice header. The scaled motion vector for the temporal mergecandidate is obtained as illustrated by the dotted line in FIG. 1C. Thescaled motion vector is derived from the motion vector of the co-locatedCU using the picture order count (POC) distances tb and td, where tb isdefined as the POC difference between a reference picture of the currentpicture and the current picture and td is defined as the POC differencebetween a reference picture of the co-located picture and the co-locatedpicture. The reference picture index of the temporal merge candidate canbe set equal to zero.

FIG. 1D shows exemplary positions for the temporal merge candidate. Thetemporal merge candidate is selected between CUs at positions C0 and C1.If the CU at position C0 is not available, not inter coded, or outsideof the current row of CTUs, the CU at position C1 is used. Otherwise,the CU at position C0 is used in the derivation of the temporal mergecandidate.

SUMMARY

Aspects of the disclosure provide methods and apparatuses for videoencoding/decoding. In some examples, an apparatus for video decodingincludes processing circuitry.

According to aspects of the disclosure, there is provided a method forvideo decoding in a decoder. In the method, prediction information of acurrent block of a current picture in a coded bitstream is decoded. Theprediction information indicates a geometric partitioning mode (GPM) forthe current block. The current block is partitioned into two partitionsin the GPM mode. Each of the partitions is associated with a respectivepredictor. A weighting index for a sample of the current block isdetermined based on a position of the sample. A weighting factor iscalculated based on the weighting index of the sample according to anequation that converts the weighting index to the weighting factor. Thesample is reconstructed based on the weighting factor and the predictorcorresponding to the sample.

In an embodiment, a right shift operation is performed on a sum of theweighting index and an offset value. A result of the right shiftoperation is clipped to be within a predefined range.

In an embodiment, the offset value is based on a number of bits shiftedby the right shift operation, and the number of bits shifted by theright shift operation is based on at least one of the weighting indexand a size of a cosine table used to calculate the weighting index.

In an embodiment, an angle index and a distance index that define asplit boundary between the partitions of the current block aredetermined based on the GPM. The weighting index for the sample isdetermined based on the position of the sample, the angle index, and thedistance index.

In an embodiment, a partition index is determined based on the angleindex. The weighting factor is calculated based on the partition index.

In an embodiment, the equation is

weight=Clip3(0,8,(wIdxL+(1<<(idx2wShiftBit−1)))>>idx2wShiftBit),

in which

wIdxL=(1<<(idx2wShiftBit+2))+(partIdx?wIdx:−wIdx),

where idx2wShiftBit indicates the number of bits shifted by the rightshift operation, weight is the weighting factor, partIdx is thepartition index, wIdx is the weighting index, and Clip3( ) is a clipfunction.

In an embodiment, the equation is a piecewise constant function thatincludes an initial value and a plurality of unit-step functions. Theinitial value is one of a minimum weighting factor value and a maximumweighting factor value, and a number of the plurality of unit-stepfunctions is equal to a total number of different weighting factorvalues minus one.

Aspects of the disclosure provide an apparatus configured to perform anyone or a combination of the methods for video decoding. In anembodiment, the apparatus includes processing circuitry that decodesprediction information of a current block of a current picture in acoded bitstream. The prediction information indicates a geometricpartitioning mode (GPM) for the current block. The current block ispartitioned into two partitions in the GPM mode. Each of the partitionsis associated with a respective predictor. The processing circuitrydetermines a weighting index for a sample of the current block based ona position of the sample. The processing circuitry calculates aweighting factor based on the weighting index of the sample according toan equation that converts the weighting index to the weighting factor.The processing circuitry reconstructs the sample based on the weightingfactor and the predictor corresponding to the sample.

Aspects of the disclosure also provide a non-transitorycomputer-readable medium storing instructions which when executed by acomputer for video decoding cause the computer to perform any one or acombination of the methods for video decoding.

BRIEF DESCRIPTION OF THE DRAWINGS

Further features, the nature, and various advantages of the disclosedsubject matter will be more apparent from the following detaileddescription and the accompanying drawings in which:

FIG. 1A shows exemplary positions of spatial merge candidates;

FIG. 1B shows exemplary candidate pairs considered for a redundancycheck of the spatial merge candidates;

FIG. 1C shows an example of motion vector scaling for a temporal mergecandidate;

FIG. 1D shows exemplary positions for the temporal merge candidate;

FIG. 2 shows a schematic illustration of a simplified block diagram of acommunication system in accordance with an embodiment;

FIG. 3 shows a schematic illustration of a simplified block diagram of acommunication system in accordance with an embodiment;

FIG. 4 shows a schematic illustration of a simplified block diagram of adecoder in accordance with an embodiment;

FIG. 5 shows a schematic illustration of a simplified block diagram ofan encoder in accordance with an embodiment;

FIG. 6 shows a block diagram of an encoder in accordance with anotherembodiment;

FIG. 7 shows a block diagram of a decoder in accordance with anotherembodiment;

FIGS. 8A and 8B show two exemplary triangular partitions in accordancewith some embodiments;

FIG. 9 shows a uni-prediction motion vector selection for the trianglepartition mode in accordance with some embodiments;

FIGS. 10A and 10B show exemplary weight maps for luma and chroma inaccordance with some embodiments;

FIG. 11 shows an exemplary geometric partitioning mode according to someembodiments of the disclosure;

FIG. 12 shows a flow chart outlining an exemplary process in accordancewith an embodiment; and

FIG. 13 shows a schematic illustration of a computer system inaccordance with an embodiment.

DETAILED DESCRIPTION OF EMBODIMENTS

The present disclosure includes embodiments directed to geometric mergemode (GEO), which can also be referred to as geometric partitioning mode(GPM). The embodiments include methods, apparatuses, and non-transitorycomputer-readable storage mediums for improving the GEO. In addition, ablock may refer to a prediction block, a coding block, or a coding unit.

I. Video Encoder and Decoder

FIG. 2 illustrates a simplified block diagram of a communication system(200) according to an embodiment of the present disclosure. Thecommunication system (200) includes a plurality of terminal devices thatcan communicate with each other, via, for example, a network (250). Forexample, the communication system (200) includes a first pair ofterminal devices (210) and (220) interconnected via the network (250).In the FIG. 2 example, the first pair of terminal devices (210) and(220) performs unidirectional transmission of data. For example, theterminal device (210) may code video data (e.g., a stream of videopictures that are captured by the terminal device (210)) fortransmission to the other terminal device (220) via the network (250).The encoded video data can be transmitted in the form of one or morecoded video bitstreams. The terminal device (220) may receive the codedvideo data from the network (250), decode the coded video data torecover the video pictures and display video pictures according to therecovered video data. Unidirectional data transmission may be common inmedia serving applications and the like.

In another example, the communication system (200) includes a secondpair of terminal devices (230) and (240) that performs bidirectionaltransmission of coded video data that may occur, for example, duringvideoconferencing. For bidirectional transmission of data, in anexample, each terminal device of the terminal devices (230) and (240)may code video data (e.g., a stream of video pictures that are capturedby the terminal device) for transmission to the other terminal device ofthe terminal devices (230) and (240) via the network (250). Eachterminal device of the terminal devices (230) and (240) also may receivethe coded video data transmitted by the other terminal device of theterminal devices (230) and (240), and may decode the coded video data torecover the video pictures and may display video pictures at anaccessible display device according to the recovered video data.

In the FIG. 2 example, the terminal devices (210), (220), (230) and(240) may be illustrated as servers, personal computers and smart phonesbut the principles of the present disclosure may be not so limited.Embodiments of the present disclosure find application with laptopcomputers, tablet computers, media players and/or dedicated videoconferencing equipment. The network (250) represents any number ofnetworks that convey coded video data among the terminal devices (210),(220), (230) and (240), including for example wireline (wired) and/orwireless communication networks. The communication network (250) mayexchange data in circuit-switched and/or packet-switched channels.Representative networks include telecommunications networks, local areanetworks, wide area networks and/or the Internet. For the purposes ofthe present discussion, the architecture and topology of the network(250) may be immaterial to the operation of the present disclosureunless explained herein below.

FIG. 3 illustrates, as an example for an application for the disclosedsubject matter, the placement of a video encoder and a video decoder ina streaming environment. The disclosed subject matter can be equallyapplicable to other video enabled applications, including, for example,video conferencing, digital TV, storing of compressed video on digitalmedia including CD, DVD, memory stick, and the like.

A streaming system may include a capture subsystem (313) that caninclude a video source (301), for example a digital camera, creating forexample a stream of video pictures (302) that are uncompressed. In anexample, the stream of video pictures (302) includes samples that aretaken by the digital camera. The stream of video pictures (302),depicted as a bold line to emphasize a high data volume when compared toencoded video data (304) (or coded video bitstreams), can be processedby an electronic device (320) that includes a video encoder (303)coupled to the video source (301). The video encoder (303) can includehardware, software, or a combination thereof to enable or implementaspects of the disclosed subject matter as described in more detailbelow. The encoded video data (304) (or encoded video bitstream (304)),depicted as a thin line to emphasize the lower data volume when comparedto the stream of video pictures (302), can be stored on a streamingserver (305) for future use. One or more streaming client subsystems,such as client subsystems (306) and (308) in FIG. 3 can access thestreaming server (305) to retrieve copies (307) and (309) of the encodedvideo data (304). A client subsystem (306) can include a video decoder(310), for example, in an electronic device (330). The video decoder(310) decodes the incoming copy (307) of the encoded video data andcreates an outgoing stream of video pictures (311) that can be renderedon a display (312) (e.g., display screen) or other rendering device (notdepicted). In some streaming systems, the encoded video data (304),(307), and (309) (e.g., video bitstreams) can be encoded according tocertain video coding/compression standards. Examples of those standardsinclude ITU-T Recommendation H.265. In an example, a video codingstandard under development is informally known as Versatile Video Coding(VVC). The disclosed subject matter may be used in the context of VVC.

It is noted that the electronic devices (320) and (330) can includeother components (not shown). For example, the electronic device (320)can include a video decoder (not shown) and the electronic device (330)can include a video encoder (not shown) as well.

FIG. 4 shows a block diagram of a video decoder (410) according to anembodiment of the present disclosure. The video decoder (410) can beincluded in an electronic device (430). The electronic device (430) caninclude a receiver (431) (e.g., receiving circuitry). The video decoder(410) can be used in the place of the video decoder (310) in the FIG. 3example.

The receiver (431) may receive one or more coded video sequences to bedecoded by the video decoder (410); in the same or another embodiment,one coded video sequence at a time, where the decoding of each codedvideo sequence is independent from other coded video sequences. Thecoded video sequence may be received from a channel (401), which may bea hardware/software link to a storage device which stores the encodedvideo data. The receiver (431) may receive the encoded video data withother data, for example, coded audio data and/or ancillary data streams,that may be forwarded to their respective using entities (not depicted).The receiver (431) may separate the coded video sequence from the otherdata. To combat network jitter, a buffer memory (415) may be coupled inbetween the receiver (431) and an entropy decoder/parser (420) (“parser(420)” henceforth). In certain applications, the buffer memory (415) ispart of the video decoder (410). In others, it can be outside of thevideo decoder (410) (not depicted). In still others, there can be abuffer memory (not depicted) outside of the video decoder (410), forexample to combat network jitter, and in addition another buffer memory(415) inside the video decoder (410), for example to handle playouttiming. When the receiver (431) is receiving data from a store/forwarddevice of sufficient bandwidth and controllability, or from anisosynchronous network, the buffer memory (415) may not be needed, orcan be small. For use on best effort packet networks such as theInternet, the buffer memory (415) may be required, can be comparativelylarge and can be advantageously of adaptive size, and may at leastpartially be implemented in an operating system or similar elements (notdepicted) outside of the video decoder (410).

The video decoder (410) may include the parser (420) to reconstructsymbols (421) from the coded video sequence. Categories of those symbolsinclude information used to manage operation of the video decoder (410),and potentially information to control a rendering device such as arender device (412) (e.g., a display screen) that is not an integralpart of the electronic device (430) but can be coupled to the electronicdevice (430), as was shown in FIG. 4. The control information for therendering device(s) may be in the form of Supplemental EnhancementInformation (SEI messages) or Video Usability Information (VUI)parameter set fragments (not depicted). The parser (420) mayparse/entropy-decode the coded video sequence that is received. Thecoding of the coded video sequence can be in accordance with a videocoding technology or standard, and can follow various principles,including variable length coding, Huffman coding, arithmetic coding withor without context sensitivity, and so forth. The parser (420) mayextract from the coded video sequence, a set of subgroup parameters forat least one of the subgroups of pixels in the video decoder, based uponat least one parameter corresponding to the group. Subgroups can includeGroups of Pictures (GOPs), pictures, tiles, slices, macroblocks, CodingUnits (CUs), blocks, Transform Units (TUs), Prediction Units (PUs) andso forth. The parser (420) may also extract from the coded videosequence information such as transform coefficients, quantizer parametervalues, motion vectors, and so forth.

The parser (420) may perform an entropy decoding/parsing operation onthe video sequence received from the buffer memory (415), so as tocreate symbols (421).

Reconstruction of the symbols (421) can involve multiple different unitsdepending on the type of the coded video picture or parts thereof (suchas: inter and intra picture, inter and intra block), and other factors.Which units are involved, and how, can be controlled by the subgroupcontrol information that was parsed from the coded video sequence by theparser (420). The flow of such subgroup control information between theparser (420) and the multiple units below is not depicted for clarity.

Beyond the functional blocks already mentioned, the video decoder (410)can be conceptually subdivided into a number of functional units asdescribed below. In a practical implementation operating undercommercial constraints, many of these units interact closely with eachother and can, at least partly, be integrated into each other. However,for the purpose of describing the disclosed subject matter, theconceptual subdivision into the functional units below is appropriate.

A first unit is the scaler/inverse transform unit (451). Thescaler/inverse transform unit (451) receives a quantized transformcoefficient as well as control information, including which transform touse, block size, quantization factor, quantization scaling matrices,etc. as symbol(s) (421) from the parser (420). The scaler/inversetransform unit (451) can output blocks comprising sample values that canbe input into aggregator (455).

In some cases, the output samples of the scaler/inverse transform (451)can pertain to an intra coded block; that is: a block that is not usingpredictive information from previously reconstructed pictures, but canuse predictive information from previously reconstructed parts of thecurrent picture. Such predictive information can be provided by an intrapicture prediction unit (452). In some cases, the intra pictureprediction unit (452) generates a block of the same size and shape ofthe block under reconstruction, using surrounding already reconstructedinformation fetched from the current picture buffer (458). The currentpicture buffer (458) buffers, for example, partly reconstructed currentpicture and/or fully reconstructed current picture. The aggregator(455), in some cases, adds, on a per sample basis, the predictioninformation that the intra prediction unit (452) has generated to theoutput sample information as provided by the scaler/inverse transformunit (451).

In other cases, the output samples of the scaler/inverse transform unit(451) can pertain to an inter coded, and potentially motion compensatedblock. In such a case, a motion compensation prediction unit (453) canaccess reference picture memory (457) to fetch samples used forprediction. After motion compensating the fetched samples in accordancewith the symbols (421) pertaining to the block, these samples can beadded by the aggregator (455) to the output of the scaler/inversetransform unit (451) (in this case called the residual samples orresidual signal) so as to generate output sample information. Theaddresses within the reference picture memory (457) from where themotion compensation prediction unit (453) fetches prediction samples canbe controlled by motion vectors, available to the motion compensationprediction unit (453) in the form of symbols (421) that can have, forexample X, Y, and reference picture components. Motion compensation alsocan include interpolation of sample values as fetched from the referencepicture memory (457) when sub-sample exact motion vectors are in use,motion vector prediction mechanisms, and so forth.

The output samples of the aggregator (455) can be subject to variousloop filtering techniques in the loop filter unit (456). Videocompression technologies can include in-loop filter technologies thatare controlled by parameters included in the coded video sequence (alsoreferred to as coded video bitstream) and made available to the loopfilter unit (456) as symbols (421) from the parser (420), but can alsobe responsive to meta-information obtained during the decoding ofprevious (in decoding order) parts of the coded picture or coded videosequence, as well as responsive to previously reconstructed andloop-filtered sample values.

The output of the loop filter unit (456) can be a sample stream that canbe output to the render device (412) as well as stored in the referencepicture memory (457) for use in future inter-picture prediction.

Certain coded pictures, once fully reconstructed, can be used asreference pictures for future prediction. For example, once a codedpicture corresponding to a current picture is fully reconstructed andthe coded picture has been identified as a reference picture (by, forexample, the parser (420)), the current picture buffer (458) can becomea part of the reference picture memory (457), and a fresh currentpicture buffer can be reallocated before commencing the reconstructionof the following coded picture.

The video decoder (410) may perform decoding operations according to apredetermined video compression technology in a standard, such as ITU-TRec. H.265. The coded video sequence may conform to a syntax specifiedby the video compression technology or standard being used, in the sensethat the coded video sequence adheres to both the syntax of the videocompression technology or standard and the profiles as documented in thevideo compression technology or standard. Specifically, a profile canselect certain tools as the only tools available for use under thatprofile from all the tools available in the video compression technologyor standard. Also necessary for compliance can be that the complexity ofthe coded video sequence is within bounds as defined by the level of thevideo compression technology or standard. In some cases, levels restrictthe maximum picture size, maximum frame rate, maximum reconstructionsample rate (measured in, for example megasamples per second), maximumreference picture size, and so on. Limits set by levels can, in somecases, be further restricted through Hypothetical Reference Decoder(HRD) specifications and metadata for HRD buffer management signaled inthe coded video sequence.

In an embodiment, the receiver (431) may receive additional (redundant)data with the encoded video. The additional data may be included as partof the coded video sequence(s). The additional data may be used by thevideo decoder (410) to properly decode the data and/or to moreaccurately reconstruct the original video data. Additional data can bein the form of, for example, temporal, spatial, or signal noise ratio(SNR) enhancement layers, redundant slices, redundant pictures, forwarderror correction codes, and so on.

FIG. 5 shows a block diagram of a video encoder (503) according to anembodiment of the present disclosure. The video encoder (503) isincluded in an electronic device (520). The electronic device (520)includes a transmitter (540) (e.g., transmitting circuitry). The videoencoder (503) can be used in the place of the video encoder (303) in theFIG. 3 example.

The video encoder (503) may receive video samples from a video source(501) (that is not part of the electronic device (520) in the FIG. 5example) that may capture video image(s) to be coded by the videoencoder (503). In another example, the video source (501) is a part ofthe electronic device (520).

The video source (501) may provide the source video sequence to be codedby the video encoder (503) in the form of a digital video sample streamthat can be of any suitable bit depth (for example: 8 bit, 10 bit, 12bit, . . . ), any colorspace (for example, BT.601 Y CrCB, RGB, . . . ),and any suitable sampling structure (for example Y CrCb 4:2:0, Y CrCb4:4:4). In a media serving system, the video source (501) may be astorage device storing previously prepared video. In a videoconferencingsystem, the video source (501) may be a camera that captures local imageinformation as a video sequence. Video data may be provided as aplurality of individual pictures that impart motion when viewed insequence. The pictures themselves may be organized as a spatial array ofpixels, wherein each pixel can comprise one or more samples depending onthe sampling structure, color space, etc. in use. A person skilled inthe art can readily understand the relationship between pixels andsamples. The description below focuses on samples.

According to an embodiment, the video encoder (503) may code andcompress the pictures of the source video sequence into a coded videosequence (543) in real time or under any other time constraints asrequired by the application. Enforcing appropriate coding speed is onefunction of a controller (550). In some embodiments, the controller(550) controls other functional units as described below and isfunctionally coupled to the other functional units. The coupling is notdepicted for clarity. Parameters set by the controller (550) can includerate control related parameters (picture skip, quantizer, lambda valueof rate-distortion optimization techniques, . . . ), picture size, groupof pictures (GOP) layout, maximum motion vector allowed reference area,and so forth. The controller (550) can be configured to have othersuitable functions that pertain to the video encoder (503) optimized fora certain system design.

In some embodiments, the video encoder (503) is configured to operate ina coding loop. As an oversimplified description, in an example, thecoding loop can include a source coder (530) (e.g., responsible forcreating symbols, such as a symbol stream, based on an input picture tobe coded, and a reference picture(s)), and a (local) decoder (533)embedded in the video encoder (503). The decoder (533) reconstructs thesymbols to create the sample data in a similar manner as a (remote)decoder also would create (as any compression between symbols and codedvideo bitstream is lossless in the video compression technologiesconsidered in the disclosed subject matter). The reconstructed samplestream (sample data) is input to the reference picture memory (534). Asthe decoding of a symbol stream leads to bit-exact results independentof decoder location (local or remote), the content in the referencepicture memory (534) is also bit exact between the local encoder andremote encoder. In other words, the prediction part of an encoder “sees”as reference picture samples exactly the same sample values as a decoderwould “see” when using prediction during decoding. This fundamentalprinciple of reference picture synchronicity (and resulting drift, ifsynchronicity cannot be maintained, for example because of channelerrors) is used in some related arts as well.

The operation of the “local” decoder (533) can be the same as of a“remote” decoder, such as the video decoder (410), which has alreadybeen described in detail above in conjunction with FIG. 4. Brieflyreferring also to FIG. 4, however, as symbols are available andencoding/decoding of symbols to a coded video sequence by an entropycoder (545) and the parser (420) can be lossless, the entropy decodingparts of the video decoder (410), including the buffer memory (415) andthe parser (420) may not be fully implemented in the local decoder(533).

An observation that can be made at this point is that any decodertechnology except the parsing/entropy decoding that is present in adecoder also necessarily needs to be present, in substantially identicalfunctional form, in a corresponding encoder. For this reason, thedisclosed subject matter focuses on decoder operation. The descriptionof encoder technologies can be abbreviated as they are the inverse ofthe comprehensively described decoder technologies. Only in certainareas a more detail description is required and provided below.

During operation, in some examples, the source coder (530) may performmotion compensated predictive coding, which codes an input picturepredictively with reference to one or more previously coded picture fromthe video sequence that were designated as “reference pictures.” In thismanner, the coding engine (532) codes differences between pixel blocksof an input picture and pixel blocks of reference picture(s) that may beselected as prediction reference(s) to the input picture.

The local video decoder (533) may decode coded video data of picturesthat may be designated as reference pictures, based on symbols createdby the source coder (530). Operations of the coding engine (532) mayadvantageously be lossy processes. When the coded video data may bedecoded at a video decoder (not shown in FIG. 5), the reconstructedvideo sequence typically may be a replica of the source video sequencewith some errors. The local video decoder (533) replicates decodingprocesses that may be performed by the video decoder on referencepictures and may cause reconstructed reference pictures to be stored inthe reference picture cache (534). In this manner, the video encoder(503) may store copies of reconstructed reference pictures locally thathave common content as the reconstructed reference pictures that will beobtained by a far-end video decoder (absent transmission errors).

The predictor (535) may perform prediction searches for the codingengine (532). That is, for a new picture to be coded, the predictor(535) may search the reference picture memory (534) for sample data (ascandidate reference pixel blocks) or certain metadata such as referencepicture motion vectors, block shapes, and so on, that may serve as anappropriate prediction reference for the new pictures. The predictor(535) may operate on a sample block-by-pixel block basis to findappropriate prediction references. In some cases, as determined bysearch results obtained by the predictor (535), an input picture mayhave prediction references drawn from multiple reference pictures storedin the reference picture memory (534).

The controller (550) may manage coding operations of the source coder(530), including, for example, setting of parameters and subgroupparameters used for encoding the video data.

Output of all aforementioned functional units may be subjected toentropy coding in the entropy coder (545). The entropy coder (545)translates the symbols as generated by the various functional units intoa coded video sequence, by lossless compressing the symbols according totechnologies such as Huffman coding, variable length coding, arithmeticcoding, and so forth.

The transmitter (540) may buffer the coded video sequence(s) as createdby the entropy coder (545) to prepare for transmission via acommunication channel (560), which may be a hardware/software link to astorage device which would store the encoded video data. The transmitter(540) may merge coded video data from the video coder (503) with otherdata to be transmitted, for example, coded audio data and/or ancillarydata streams (sources not shown).

The controller (550) may manage operation of the video encoder (503).During coding, the controller (550) may assign to each coded picture acertain coded picture type, which may affect the coding techniques thatmay be applied to the respective picture. For example, pictures oftenmay be assigned as one of the following picture types:

An Intra Picture (I picture) may be one that may be coded and decodedwithout using any other picture in the sequence as a source ofprediction. Some video codecs allow for different types of intrapictures, including, for example Independent Decoder Refresh (“IDR”)Pictures. A person skilled in the art is aware of those variants of Ipictures and their respective applications and features.

A predictive picture (P picture) may be one that may be coded anddecoded using intra prediction or inter prediction using at most onemotion vector and reference index to predict the sample values of eachblock.

A bi-directionally predictive picture (B Picture) may be one that may becoded and decoded using intra prediction or inter prediction using atmost two motion vectors and reference indices to predict the samplevalues of each block. Similarly, multiple-predictive pictures can usemore than two reference pictures and associated metadata for thereconstruction of a single block.

Source pictures commonly may be subdivided spatially into a plurality ofsample blocks (for example, blocks of 4×4, 8×8, 4×8, or 16×16 sampleseach) and coded on a block-by-block basis. Blocks may be codedpredictively with reference to other (already coded) blocks asdetermined by the coding assignment applied to the blocks' respectivepictures. For example, blocks of I pictures may be codednon-predictively or they may be coded predictively with reference toalready coded blocks of the same picture (spatial prediction or intraprediction). Pixel blocks of P pictures may be coded predictively, viaspatial prediction or via temporal prediction with reference to onepreviously coded reference picture. Blocks of B pictures may be codedpredictively, via spatial prediction or via temporal prediction withreference to one or two previously coded reference pictures.

The video encoder (503) may perform coding operations according to apredetermined video coding technology or standard, such as ITU-T Rec.H.265. In its operation, the video encoder (503) may perform variouscompression operations, including predictive coding operations thatexploit temporal and spatial redundancies in the input video sequence.The coded video data, therefore, may conform to a syntax specified bythe video coding technology or standard being used.

In an embodiment, the transmitter (540) may transmit additional datawith the encoded video. The source coder (530) may include such data aspart of the coded video sequence. Additional data may comprisetemporal/spatial/SNR enhancement layers, other forms of redundant datasuch as redundant pictures and slices, SEI messages, VUI parameter setfragments, and so on.

A video may be captured as a plurality of source pictures (videopictures) in a temporal sequence. Intra-picture prediction (oftenabbreviated to intra prediction) makes use of spatial correlation in agiven picture, and inter-picture prediction makes uses of the (temporalor other) correlation between the pictures. In an example, a specificpicture under encoding/decoding, which is referred to as a currentpicture, is partitioned into blocks. When a block in the current pictureis similar to a reference block in a previously coded and still bufferedreference picture in the video, the block in the current picture can becoded by a vector that is referred to as a motion vector. The motionvector points to the reference block in the reference picture, and canhave a third dimension identifying the reference picture, in casemultiple reference pictures are in use.

In some embodiments, a bi-prediction technique can be used in theinter-picture prediction. According to the bi-prediction technique, tworeference pictures, such as a first reference picture and a secondreference picture that are both prior in decoding order to the currentpicture in the video (but may be in the past and future, respectively,in display order) are used. A block in the current picture can be codedby a first motion vector that points to a first reference block in thefirst reference picture, and a second motion vector that points to asecond reference block in the second reference picture. The block can bepredicted by a combination of the first reference block and the secondreference block.

Further, a merge mode technique can be used in the inter-pictureprediction to improve coding efficiency.

According to some embodiments of the disclosure, predictions, such asinter-picture predictions and intra-picture predictions are performed inthe unit of blocks. For example, according to the HEVC standard, apicture in a sequence of video pictures is partitioned into coding treeunits (CTU) for compression, the CTUs in a picture have the same size,such as 64×64 pixels, 32×32 pixels, or 16×16 pixels. In general, a CTUincludes three coding tree blocks (CTBs), which are one luma CTB and twochroma CTBs. Each CTU can be recursively quad-tree split into one ormultiple CUs. For example, a CTU of 64×64 pixels can be split into oneCU of 64×64 pixels, or 4 CUs of 32×32 pixels, or 16 CUs of 16×16 pixels.In an example, each CU is analyzed to determine a prediction type forthe CU, such as an inter prediction type or an intra prediction type.The CU is split into one or more prediction units (PUs) depending on thetemporal and/or spatial predictability. Generally, each PU includes aluma prediction block (PB), and two chroma PBs. In an embodiment, aprediction operation in coding (encoding/decoding) is performed in theunit of a prediction block. Using a luma prediction block as an exampleof a prediction block, the prediction block includes a matrix of values(e.g., luma values) for pixels, such as 8×8 pixels, 16×16 pixels, 8×16pixels, 16×8 pixels, and the like.

FIG. 6 shows a diagram of a video encoder (603) according to anotherembodiment of the disclosure. The video encoder (603) is configured toreceive a processing block (e.g., a prediction block) of sample valueswithin a current video picture in a sequence of video pictures, andencode the processing block into a coded picture that is part of a codedvideo sequence. In an example, the video encoder (603) is used in theplace of the video encoder (303) in the FIG. 3 example.

In an HEVC example, the video encoder (603) receives a matrix of samplevalues for a processing block, such as a prediction block of 8×8samples, and the like. The video encoder (603) determines whether theprocessing block is best coded using intra mode, inter mode, orbi-prediction mode using, for example, rate-distortion optimization.When the processing block is to be coded in intra mode, the videoencoder (603) may use an intra prediction technique to encode theprocessing block into the coded picture; and when the processing blockis to be coded in inter mode or bi-prediction mode, the video encoder(603) may use an inter prediction or bi-prediction technique,respectively, to encode the processing block into the coded picture. Incertain video coding technologies, merge mode can be an inter pictureprediction submode where the motion vector is derived from one or moremotion vector predictors without the benefit of a coded motion vectorcomponent outside the predictors. In certain other video codingtechnologies, a motion vector component applicable to the subject blockmay be present. In an example, the video encoder (603) includes othercomponents, such as a mode decision module (not shown) to determine themode of the processing blocks.

In the FIG. 6 example, the video encoder (603) includes the interencoder (630), an intra encoder (622), a residue calculator (623), aswitch (626), a residue encoder (624), a general controller (621), andan entropy encoder (625) coupled together as shown in FIG. 6.

The inter encoder (630) is configured to receive the samples of thecurrent block (e.g., a processing block), compare the block to one ormore reference blocks in reference pictures (e.g., blocks in previouspictures and later pictures), generate inter prediction information(e.g., description of redundant information according to inter encodingtechnique, motion vectors, merge mode information), and calculate interprediction results (e.g., predicted block) based on the inter predictioninformation using any suitable technique. In some examples, thereference pictures are decoded reference pictures that are decoded basedon the encoded video information.

The intra encoder (622) is configured to receive the samples of thecurrent block (e.g., a processing block), in some cases compare theblock to blocks already coded in the same picture, generate quantizedcoefficients after transform, and in some cases also intra predictioninformation (e.g., an intra prediction direction information accordingto one or more intra encoding techniques). In an example, the intraencoder (622) also calculates intra prediction results (e.g., predictedblock) based on the intra prediction information and reference blocks inthe same picture.

The general controller (621) is configured to determine general controldata and control other components of the video encoder (603) based onthe general control data. In an example, the general controller (621)determines the mode of the block, and provides a control signal to theswitch (626) based on the mode. For example, when the mode is the intramode, the general controller (621) controls the switch (626) to selectthe intra mode result for use by the residue calculator (623), andcontrols the entropy encoder (625) to select the intra predictioninformation and include the intra prediction information in thebitstream; and when the mode is the inter mode, the general controller(621) controls the switch (626) to select the inter prediction resultfor use by the residue calculator (623), and controls the entropyencoder (625) to select the inter prediction information and include theinter prediction information in the bitstream.

The residue calculator (623) is configured to calculate a difference(residue data) between the received block and prediction resultsselected from the intra encoder (622) or the inter encoder (630). Theresidue encoder (624) is configured to operate based on the residue datato encode the residue data to generate the transform coefficients. In anexample, the residue encoder (624) is configured to convert the residuedata from a spatial domain to a frequency domain, and generate thetransform coefficients. The transform coefficients are then subject toquantization processing to obtain quantized transform coefficients. Invarious embodiments, the video encoder (603) also includes a residuedecoder (628). The residue decoder (628) is configured to performinverse-transform, and generate the decoded residue data. The decodedresidue data can be suitably used by the intra encoder (622) and theinter encoder (630). For example, the inter encoder (630) can generatedecoded blocks based on the decoded residue data and inter predictioninformation, and the intra encoder (622) can generate decoded blocksbased on the decoded residue data and the intra prediction information.The decoded blocks are suitably processed to generate decoded picturesand the decoded pictures can be buffered in a memory circuit (not shown)and used as reference pictures in some examples.

The entropy encoder (625) is configured to format the bitstream toinclude the encoded block. The entropy encoder (625) is configured toinclude various information according to a suitable standard, such asthe HEVC standard. In an example, the entropy encoder (625) isconfigured to include the general control data, the selected predictioninformation (e.g., intra prediction information or inter predictioninformation), the residue information, and other suitable information inthe bitstream. Note that, according to the disclosed subject matter,when coding a block in the merge submode of either inter mode orbi-prediction mode, there is no residue information.

FIG. 7 shows a diagram of a video decoder (710) according to anotherembodiment of the disclosure. The video decoder (710) is configured toreceive coded pictures that are part of a coded video sequence, anddecode the coded pictures to generate reconstructed pictures. In anexample, the video decoder (710) is used in the place of the videodecoder (310) in the FIG. 3 example.

In the FIG. 7 example, the video decoder (710) includes an entropydecoder (771), an inter decoder (780), a residue decoder (773), areconstruction module (774), and an intra decoder (772) coupled togetheras shown in FIG. 7.

The entropy decoder (771) can be configured to reconstruct, from thecoded picture, certain symbols that represent the syntax elements ofwhich the coded picture is made up. Such symbols can include, forexample, the mode in which a block is coded (such as, for example, intramode, inter mode, bi-predicted mode, the latter two in merge submode oranother submode), prediction information (such as, for example, intraprediction information or inter prediction information) that canidentify certain sample or metadata that is used for prediction by theintra decoder (772) or the inter decoder (780), respectively, residualinformation in the form of, for example, quantized transformcoefficients, and the like. In an example, when the prediction mode isinter or bi-predicted mode, the inter prediction information is providedto the inter decoder (780); and when the prediction type is the intraprediction type, the intra prediction information is provided to theintra decoder (772). The residual information can be subject to inversequantization and is provided to the residue decoder (773).

The inter decoder (780) is configured to receive the inter predictioninformation, and generate inter prediction results based on the interprediction information.

The intra decoder (772) is configured to receive the intra predictioninformation, and generate prediction results based on the intraprediction information.

The residue decoder (773) is configured to perform inverse quantizationto extract de-quantized transform coefficients, and process thede-quantized transform coefficients to convert the residual from thefrequency domain to the spatial domain. The residue decoder (773) mayalso require certain control information (to include the QuantizerParameter (QP)), and that information may be provided by the entropydecoder (771) (data path not depicted as this may be low volume controlinformation only).

The reconstruction module (774) is configured to combine, in the spatialdomain, the residual as output by the residue decoder (773) and theprediction results (as output by the inter or intra prediction modulesas the case may be) to form a reconstructed block, that may be part ofthe reconstructed picture, which in turn may be part of thereconstructed video. It is noted that other suitable operations, such asa deblocking operation and the like, can be performed to improve thevisual quality.

It is noted that the video encoders (303), (503), and (603), and thevideo decoders (310), (410), and (710) can be implemented using anysuitable technique. In an embodiment, the video encoders (303), (503),and (603), and the video decoders (310), (410), and (710) can beimplemented using one or more integrated circuits. In anotherembodiment, the video encoders (303), (503), and (603), and the videodecoders (310), (410), and (710) can be implemented using one or moreprocessors that execute software instructions.

II. Triangle Partition Mode (TPM) for Inter Prediction

In some cases, a TPM can be supported for inter prediction. The TPM canonly be applied to CUs that are 8×8 or larger. The TPM can be signaledusing a CU-level flag as one kind of merge mode, with other merge modes,such as the regular merge mode, the MMVD mode, the CIIP mode, and thesubblock merge mode.

When the TPM is used, a CU can be split evenly into two triangle-shapedpartitions, using either a diagonal split or an anti-diagonal split, asshown in FIGS. 8A and 8B for example. Each triangle partition in the CUcan be inter-predicted using its own motion parameters. Onlyuni-prediction can be allowed for each partition. That is, eachpartition has one motion vector and one reference index. Theuni-prediction motion constraint is applied to ensure that the trianglepartition is the same as the conventional bi-prediction. That is, onlytwo motion compensated predictions are needed for each CU. Theuni-prediction motion for each partition can be derived using theprocess described in FIGS. 1A-1D.

If the TPM is used for a current CU, then a flag indicating a direction(diagonal or anti-diagonal) of the TPM and two merge indices (one foreach partition) can be further signaled. The maximum TPM candidate sizecan be signaled explicitly at the slice level and specify syntaxbinarization for the TMP merge indices. After predicting each of thetriangular partitions, the sample values along the diagonal oranti-diagonal edge can be adjusted using a blending process withadaptive weighting values. After deriving the prediction signal for thewhole CU, transform and quantization process can be further applied tothe whole CU as in other prediction modes. Finally, the motion field ofthe CU that is predicted using the TPM can be stored.

In some cases, the TPM cannot be used in combination with sub-blocktransform (SBT). That is, when the signaled triangle mode is equal to 1,the cu_sbt_flag is inferred to be 0 without signaling.

The uni-prediction candidate list can be derived directly from the mergecandidate list constructed according to the extended merge predictionprocess. Denote N as the index of the uni-prediction motion in thetriangle uni-prediction candidate list. The LX motion vector of the N-thextended merge candidate, with X equal to the parity of N, is used asthe N-th uni-prediction motion vector for TPM. These motion vectors aremarked with “X” in FIG. 9. In case a corresponding LX motion vector ofthe N-the extended merge candidate does not exist, the L(1-X) motionvector of the same candidate is used instead as the uni-predictionmotion vector for TPM.

After predicting each triangular partition using its own motionparameters, the blending process can be applied to the two predictionsignals to derive samples around the diagonal or anti-diagonal edge. Thefollowing weighting values are used in the blending process: {⅞, 6/8, ⅝,4/8, ⅜, 2/8, ⅛} for luma and { 6/8, 4/8, 2/8} for chroma, as shown inFIGS. 10A and 10B.

In some cases, the motion vectors of a CU coded in TPM can be generatedusing the following process. If Mv1 and Mv2 are from different referencepicture lists (e.g., one from L0 and the other from L1), then Mv1 andMv2 are simply combined to form the bi-prediction motion vector.Otherwise, if Mv1 and Mv2 are from the same list, only uni-predictionmotion Mv2 is stored.

III. Geometric Merge Mode (GEO)

Geometric merge mode (GEO), also referred to as geometric partitioningmode (GPM), can support a plurality of different partitioning manners.The partitioning manners can be defined by angles and edges. Forexample, 140 different partitioning manners can be differentiated by 32angles (quantized between 0 and 360° with 11.25° of equal separation)and 5 edges relative to the center of a CU.

FIG. 11 shows an exemplary GEO. In FIG. 11, an angle φ_(i) represents aquantized angle between 0 and 360 degrees and a distance offset ρ_(i)represents a quantized offset of the largest distance ρ_(max). The valueof ρ_(max) can be geometrically derived by Eq. 1 for either a w or hthat is equal to 8 and scaled with log2 scaled short edge length. Thevariables h and w represent the height and width of the current block.When φ is equal to 0°, ρ_(max) is equal to w/2. When φ is equal to 90°,ρ_(max) is equal to h/2. In Eq. 1, ρ_(margin)=1.0 is to prevent thesplit boundary from being too close to the corner of the current block.

$\begin{matrix}{{{\rho_{\max}\left( {\varphi,w,h} \right)} = {{{\cos(\varphi)}\left( {\frac{h}{2\mspace{14mu}{\tan\left( {\frac{\pi}{2} - \varphi} \right)}} + \frac{w}{2}} \right)} - \rho_{margin}}},{0 < \varphi < \frac{\pi}{2}}} & \left( {{Eq}.\mspace{11mu} 1} \right)\end{matrix}$

Each partition mode (i.e., a pair of an angle index and an edge index)in GEO can be assigned with a pixel-adaptive weight table to blendsamples in the two partitioned parts. The weighting value of a samplecan range from for example 0 to 8 and be determined by the L2 distancefrom the center position of a pixel to the edge. A unit-gain constraintcan be followed when the weighting values are assigned. For example,when a small weighting value is assigned to a GEO partition, a largecomplementary one is assigned to the other partition, summing up to 8.

IV. Weighted Sample Prediction Process for GEO

In GEO, a final sample predictor P_(B) can be derived with two 3-bitblending masks (i.e., weighting values or weighting factors) W₀ and W₁and two predictors P₀ and P₁ according to Eq. 2.

P _(B)=(W ₀ P ₀ W ₁ P ₁+4)>>3  (Eq. 2)

The blending masks W₀ and W₁ can be derived from a look-up table basedon their weighting indices. A weighting index can be derived based on adistance between the sample position (x, y) and the split boundary, asshown in Eq. 3.

$\begin{matrix}{{{wIdx}\left( {x,y} \right)} = {{x \times {\cos(\varphi)}} + {y \times {\cos\left( {\varphi + \frac{\pi}{2}} \right)}} - {\left( {\rho + {\frac{w}{2} \times {\cos(\varphi)}} + {\frac{h}{2} \times {\cos\left( {\varphi + \frac{\pi}{2}} \right)}}} \right)\mspace{14mu}{where}}}} & \left( {{Eq}.\mspace{11mu} 3} \right) \\\begin{matrix}{\mspace{85mu}{\rho = {i \times \frac{\rho_{\max}\left( {\varphi,w,h} \right)}{n}}}} \\{= {i \times {\left( {{\left( {{\frac{h}{2} \times {\tan(\varphi)}} + \frac{w}{2}} \right) \times {\cos(\varphi)}} - \rho_{margin}} \right)/n}}} \\{= {i \times {\left( {{\left( {{\frac{w}{2} \times {\cos(\varphi)}} + \frac{h}{2}} \right) \times {\cos\left( {\varphi + \frac{\pi}{2}} \right)}} - \rho_{margin}} \right)/n}}}\end{matrix} & \left( {{Eq}.\mspace{11mu} 4} \right)\end{matrix}$

In Eq. 4, n represents the total distance quantization steps, and irepresents the distance step index for the GEO with the angle φ, andi<n.

Finally, the blending masks W₀ and W₁ (or the weighting values) of thesample can be set using Table 3 denoted as GeoFilter, as shown in Eq. 5.

weight(x,y)=wIdx(x,y)≤0?GeoFilter[[wIdx(x,y)]]:8−GeoFilter[[wIdx(x,y)]]  (Eq.5)

An exemplary weighted sample prediction process is described as follows.Inputs to this process include two variables nCbW and nCbH specifyingthe width and the height of the current coding block, two (nCbW)×(nCbH)arrays predSamplesLA and predSamplesLB, a variable angleIdx specifyingthe angle index of the geometric partition, a variable distanceIdxspecifying the distance idx of the geometric partition, and a variablecIdx specifying a color component index. Outputs of this process includea (nCbW)×(nCbH) array pbSamples of prediction sample values and a(nCbW>>2)×(nCbH>>2) array motionIdx.

The variable bitDepth can be derived as follows: if cIdx=0,bitDepth=BitDepthY; otherwise, bitDepth=BitDepthC.

The variables shift1=Max(5, 17−bitDepth) and offset1=1<<(shift1−1).

The weights array sampleWeightL[x][y] for luma and sampleWeightC[x][y]for chroma with x=0 . . . nCbW−1 and y=0 . . . nCbH−1 can be derived asfollows:

The variables wIdx=log2(nCbW) and hIdx=log2(nCbH).

The variable whRatio=(wIdx>=hIdx)?wIdx−hIdx:hIdx−wIdx,scaleIdx=(wIdx>=hIdx)?hIdx−3:wIdx−3.

The variables displacementX=angleIdx anddisplacementY=(displacementX+8)%32.

The variableangleN=(wIdx>=hIdx)?(angleIdx>>3&1)?angleIdx%8:8−angleIdx%8:(angleIdx>>3&1)?8−angleIdx%8:angleIdx%8.

The variable rho can be set to the following value using the look-uptables denoted as stepDis and Dis, specified in Table 1 and Table 2.

rho=distanceIdx*(stepDis[whRatio][angleN]<<scaleIdx)+(Dis[displacementX]<<wIdx)+(Dis[displacementY]<<hIdx).

The variable weightIdx and weightIdxAbs can be calculated using thelook-up Table 2 with x=0 . . . nCbW−1 and y=0 . . . nCbH−1.

weightIdx=((x<<1)+1)*Dis[displacementX]+((y<<1)+1))*Dis[displacementY]−rho.

weightIdxAbs=Clip3(0,26,(abs(weightIdx)+4)>>3).

The variable partIdx can be set to weightIdx>0, if x=0 and y=nCbH−1.

The value of sampleWeightL[x][y] with x=0 . . . nCbW−1 and y=0 . . .nCbH−1 can be set according to Table 3 denoted as GeoFilter.

sampleWeightL[x][y]=weightIdx<=0?GeoFilter[weightIdxAbs]:8−GeoFilter[weightIdxAbs].

The value sampleWeightC[x][y] with x =0 . . . nCbW−1 and y=0 . . .nCbH−1 can be set as follows:sampleWeightC[x][y]=sampleWeightL[(x<<(SubWidthC−1))][(y<<(SubHeightC−1))].

TABLE 1 whRatio 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 angleN 0 1 2 3 4 5 67 8 0 1 2 3 4 5 6 7 8 stepDis[whRatio] 77 95 108 116 119 116 108 95 7777 115 147 173 192 202 203 195 179 [ angleN] whRatio 2 2 2 2 2 2 2 2 2 33 3 3 3 3 3 3 3 angleN 0 1 2 3 4 5 6 7 8 0 1 2 3 4 5 6 7 8stepDis[whRatio] 77 155 226 287 336 372 392 396 384 77 235 382 515 626712 770 798 794 [ angleN]

TABLE 2 idx 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Dis[idx] 64 63 59 5345 36 24 12 0 −12 −24 −36 −45 −53 −59 −63 idx 16 17 18 19 20 21 22 23 2425 26 27 28 29 30 31 Dis[idx] −64 −63 −59 −53 −45 −36 −24 −12 0 12 24 3645 53 59 63

TABLE 3 idx 0 1 2 3 4 5 6 7 8 9 10 11 12 13 GeoFilter[idx] 4 4 4 4 5 5 55 5 5 5 6 6 6 idx 14 15 16 17 18 19 20 21 22 23 24 25 26 GeoFilter[idx]6 6 6 6 7 7 7 7 7 7 7 7 8

In order to reduce the storage requirement of the precalculated blendingmasks, a minimum blending mask storage method can achieve an 84-91%memory requirement reduction for the blending weights storage.

Let g_sampleWeight_(L) [] represent the pre-defined masks for blendingweights. Assuming that N represents the number of pre-defined masks ineach set, and N is set to NA>>1, where NA is the number of anglessupported in GEO. M×M represents the size of the pre-defined masks forthe blending weights, and M is set to 128+((ND−1)×(128>>S))<<1, where NDis the number of steps supported in GEO and S is set to ND−1. For the 32angles with 5 steps setting, N is set to 16 and M is set to 192. For the24 angles with 4 steps setting, N is set to 12 and M is set to 224.

For a block of size W×H with geometric partitioning index K, theblending weights for luma samples are derived as follows. Variablesangle φ and distance ρ are obtained from a look-up table using thegeometric partitioning index K. Variables offsetX and offsetY can becalculated as follows:

$\begin{matrix}{\mspace{76mu}{{offsetX} = \left\{ \begin{matrix}\begin{matrix}{{\left( {M - W} \right) ⪢ 1},{{\varphi\mspace{14mu}\%\mspace{20mu} N} = {8\mspace{14mu}{or}}}} \\\left( {{\varphi\mspace{14mu}\%\mspace{14mu} N} \neq {0\mspace{14mu}{and}\mspace{14mu} H} \geq W} \right)\end{matrix} \\\begin{matrix}{{\left( {\left( {M - W} \right) ⪢ 1} \right) + \varphi} < {N?}} \\{{\left( {\rho \times W} \right) ⪢ {{S\text{:}} - \left( {\left( {\rho \times W} \right) ⪢ S} \right)}},{otherwise}}\end{matrix}\end{matrix} \right.}} & \left( {{Eq}.\mspace{11mu} 6} \right) \\{\mspace{79mu}\left( {{offsetY} = \left\{ \begin{matrix}{{\left( {\left( {M - H} \right) ⪢ 1} \right) + \varphi} < {{N?}\left( {\rho \times H} \right)} ⪢ {S\text{:}}} \\{{- \left( {\left( {\rho \times H} \right) ⪢ S} \right)},} \\{{\varphi\mspace{14mu}\%\mspace{14mu} N} = {8\mspace{14mu}{or}\mspace{14mu}\left( {{\varphi\mspace{14mu}\%\mspace{14mu} N} \neq {0\mspace{14mu}{and}\mspace{14mu} H} \geq W} \right)}} \\{{\left( {M - H} \right) ⪢ 1},{otherwise}}\end{matrix} \right.} \right.} & \left( {{Eq}.\mspace{11mu} 7} \right) \\{{{{sampleWeight}_{L}\lbrack x\rbrack}\lbrack y\rbrack} = {{{{g\_ sampleWeight}_{L}\left\lbrack {\varphi\mspace{14mu}\%\mspace{14mu} N} \right\rbrack}\left\lbrack {x + {offsetX}} \right\rbrack}\left\lbrack {y + {offsetY}} \right\rbrack}} & \left( {{Eq}.\mspace{11mu} 8} \right)\end{matrix}$

An exemplary weighted sample prediction process with minimum blendingweight mask storage for GEO is described as follows. Inputs to thisprocess include two variables nCbW and nCbH specifying the width and theheight of the current coding block, two (nCbW)×(nCbH) arrayspredSamplesLA and predSamplesLB, a variable angleIdx specifying theangle index of the geometric partition, a variable distanceIdxspecifying the distance idx of the geometric partition, and a variablecIdx specifying a color component index. Outputs of this process includea (nCbW)×(nCbH) array pbSamples of prediction sample values and avariable partIdx.

The variable bitDepth can be derived as follows: if cIdx=0,bitDepth=BitDepthY; otherwise, bitDepth=BitDepthC.

The variables shift1=Max(5, 17−bitDepth) and offset1=1<<(shift1−1).

The weights array sampleWeightL[x][y] for luma and sampleWeightC[x][y]for chroma with x=0 . . . nCbW−1 and y=0 . . . nCbH−1 can be derived asfollows:

The variable hwRatio=nCbH/nCbW.

The variables displacementX=angleIdx anddisplacementY=(displacementX+8)%32.

The variable partIdx=(angleIdx>=13&& angleIdx<=27)? 1:0.

The variable rho can be set to the following value using the look-upTable 2.

rho=(Dis[displacementX]<<8)+(Dis[displacementY]<<8).

If one of the following conditions is true, the variable shiftHor=0: (1)

angleIdx%16=8; and (2) angleIdx%16!=0 and hwRatio≥1. Otherwise,shiftHor=1.

If shiftHor=0, offsetX=(256−nCbW)>>1,

offsetY=(256−nCbH)>>1+angleIdx<16?(distanceIdx*nCbH)>>3:−((distanceIdx*nCbH)>>3).

Otherwise, if shiftHor=1,

offsetX=(256−nCbW)>>1+angleIdx<16?(distanceIdx*nCbW)>>3:−((distanceIdx*nCbW)>>3),

offsetY=(256−nCbH)>>1.

The variable weightIdx and weightIdxAbs can be calculated using thelook-up Table 2 with x=0 . . . nCbW−1 and y=0 . . . nCbH−1 as follows:

weightIdx=(((x+offsetX)<<1)+1)*Dis[displacementX]+(((y+offsetY)<<1)+1))*Dis[displacementY]−rho,weightIdxAbs=Clip3(0, 26, abs(weightIdx)).

The value of sampleWeightL[x][y] with x=0 . . . nCbW−1 and y=0 . . .nCbH−1 can be set according to Table 3 denoted as GeoFilter.

sampleWeightL[x][y]=weightIdx<=0?GeoFilter[weightIdxAbs]:8−GeoFilter[weightIdxAbs].

The value sampleWeightC[x][y] with x=0 . . . nCbW−1 and y=0 . . . nCbH−1can be set as follows:sampleWeightC[x][y]=sampleWeightL[(x<<(SubWidthC−1))][(y<<(SubHeightC−1))].

V. Motion Vector Storing Process for GEO

In some cases, luminance sample weights at four corners of a 4×4 motionstorage unit can be summed up. The sum can be compared with 2 thresholdsto determine whether one of two uni-prediction motion information andbi-prediction motion information is stored. The bi-prediction motioninformation can be derived using the same process as TPM.

An exemplary motion vector storage process for GEO is described asfollows.

The array motionIdx[xSbIdx][ySbIdx] with xSbIdx=0 . . . (nCbW>>2)−1 andySbIdx=0 . . . (nCbH>>2)−1 can be derived as follows:

The variables threshScaler=(wIdx+hIdx)>>1)−1,threshLower=32>>threshScaler, threshUpper=32−threshLower,Cnt=sampleWeightL[(xSbIdx<<2)][(ySbIdx<<2)]+sampleWeightL[(xSbIdx<<2)+3][(ySbIdx<<2)]+sampleWeightL[(xSbIdx<<2)][(ySbIdx<<2)+3]+sampleWeightL[(xSbIdx<<2)+3][(ySbIdx<<2)+3],Cnt=partIdx?32−Cnt:Cnt,motionIdx[xSbIdx][ySbIdx]=Cnt<=threshLower?0:Cnt>=threshUpper?1:2.

If the merge_geo_flag[xCb][yCb]=1, sType=motionIdx[xSbIdx][ySbIdx] withxSbIdx=0 . . . numSbX−1, and ySbIdx=0 . . . numSbY−1.

In some cases, the motion vector storage process is further simplified.The distance between the central position of a 4×4 motion storage unitand the split boundary can be calculated and compared with a fixedthreshold to determine whether uni- or bi-prediction motion informationis stored for the 4×4 motion storage unit. The sign of the distanceindicates which uni-prediction motion information should be stored inthe uni-prediction storage case. The dependency of blending mask andmotion storage can be removed.

If the merge_geo_flag[xCb][yCb]=1, wIdx=log2(cbWidth),hIdx=log2(cbHeight), whRatio=(wIdx>=hIdx)?wIdx−hIdx:hIdx−wIdx,scaleIdx=(wIdx>=hIdx)?hIdx−3:wIdx−3, displacementX=angleIdx,displacementY=(displacementX+8)%32,angleN=(wIdx>=hIdx)?(angleIdx>>3&1)?angleIdx%8:8−angleIdx%8:(angleIdx>>3&1)?8−angleIdx%8:angleIdx%8.

The variable rho is set to the following value using the look-up tablesdenoted as stepDis and Dis, specified in Table 1 and Table 2.

rho=distanceIdx*(stepDis[whRatio][angleN]<<scaleIdx)+(Dis[displacementX]<<wIdx)+(Dis[displacementY]<<hIdx).

The variable motionOffset is set to the following value using thelook-up tables denoted as Dis, specified in Table 1 and Table 2.

motionOffset=3*Dis[displacementX]+3*Dis[displacementY].

The variable motionldx is calculated using the look-up Table 2 asfollows:

motionIdx=((xSbIdx<<3)+1)*Dis[displacementX]+((xSbIdx<<3)+1))*Dis[displacementY]−rho+motionOffset.

The variable sType is derived as follows: if partIdx=1,

sType=abs(motionIdx)<256?2:motionIdx<=0?1:0; otherwise,

sType=abs(motionIdx)<256?2:motionIdx<=0?0:1.

To reduce the memory needed for storing the masks for motion fieldstorage, in a process, all the information from a pre-defined mask canbe derived for the masks of motion field storage. This process isinvoked when decoding a coding unit with MergeWedgeFlag[xCb][yCb]=1.Inputs to this process include a luma location (xCb, yCb) specifying thetop-left sample of the current coding block relative to the top leftluma sample of the current picture, a variable cbWidth specifying thewidth of the current coding block in luma samples, a variable cbHeightspecifying the height of the current coding block in luma samples, theluma motion vectors in 1/16 fractional-sample accuracy mvA and mvB, thereference indices refIdxA and refIdxB, and the prediction list flagspredListFlagA and predListFlagB.

The variables numSbX and numSbY specifying the number of 4×4 blocks inthe current coding block in horizontal and vertical direction are setequal to numSbX=cbWidth>>2 and numSbY=cbHeight>>2.

The variables displacementX=angleIdx,displacementY=(displacementX+8)%32, hwRatio=nCbH/nCbW.

If one of the following conditions is true, the variable shiftHor=0: (1)

angleIdx%16=8; and (2) angleIdx%16!=0 and hwRatio≥1. Otherwise,shiftHor=1.

The variable partIdx=(angleIdx>=13&&angleIdx<=27)?1:0.

If shiftHor=0, offsetX=(64−numSbX)>>1,offsetY=(64−numSbY)>>1+angleIdx<16?(distanceIdx*nCbH)>>5:−((distanceIdx*nCbH)>>5).Otherwise, if shiftHor=1,offsetX=(64−numSbX)>>1+angleIdx<16?(distanceIdx*nCbW)>>5:−((distanceIdx*nCbW)>>5),offsetY=(64−numSbY)>>1.

The value of the variable rho is derived according to the equation belowand the Dis lookup table specified in Table 2.rho=(Dis[displacementX]<<8)+(Dis[displacementY]<<8).

The variable motionOffset is set equal to the following value using thelook-up tables denoted as Dis, specified in Table 1 and Table 2.

motionOffset=3*Dis[displacementX]+3*Dis[displacementY].

For each 4×4 subblock at subblock index (xSbIdx, ySbIdx) with xSbIdx=0 .. . numSbX−1, and ySbIdx=0 . . . numSbY−1, the variable motionIdx iscalculated using the look-up Table 2 as follows:

motionIdx=(((xSbIdx+offsetX)<<3)+1)*Dis[displacementX]+(((xSbIdx+offsetY<<3)+1))*Dis[displacementY]−rho+motionOffset.

VI. On-the-Fly Weighting Index to Weighting Value Calculation

In the above weighted sample process for GEO, the weighting indexwIdx(x, y) to the weighting value (or weighting factor) weight(x, y)conversion can be derived based on a linear function, as shown in Eq.9-Eq.11.

weightIdxL(x,y)=fl2intOp(s×wIdx(x,y)+bias)  (Eq. 9)

wValue(x,y)=min(maxValue,weightIdxL(x,y))  (Eq. 10)

weight(x,y)=(wIdx(x,y)<0)?wValue(x,y):−wValue(x,y)  (Eq. 11)

In an example, maxValue=8, bias=4, the quantization step size s=1/7.2.The fl2intOp operation is used to convert a floating value to an integernumber and can be a combination of round, floor, or ceil. A look-uptable, such as Table 3, is an exemplary implementation method for theabove equations.

However, since different samples may have different input values for thelook-up table, multiple copies of the look-up table may be needed toperform parallel processing on these samples when the above equationsare used. Accordingly, the above weighted sample process for GEO is notfriendly for hardware and software implementation. To address thisissue, this disclosure includes embodiments for calculation basedconversion so that the weighting values for different samples can bederived in parallel.

According to aspects of the disclosure, the weighting index wIdx(x, y)to the weighting value weight(x, y) conversion can be derived based onan on-the-fly calculation with a right shift operation.

In some embodiments, the on-the-fly calculation is a sum of an offsetvalue and the weighting index wIdx(x, y) and the offset value is afunction of the right shift operand. In addition, the offset value canbe rounded.

In an embodiment, the weighting index wIdx(x, y) to the weighting valueweight(x, y) conversion can be derived according to Eq. 12.

weight(x,y)=(2^(idx2wshiftBit+2)−wIdx(x,y))>>idx2wShiftBit  (Eq. 12)

In Eq. 12, the offset value 2^(idx2wShiftBit+2) is an exponentialfunction (with base 2) of the right shift operand idx2wShiftBit. In anexample, the right shift operand idx2wShiftBit=m+3, and the weightingvalue weight(x, y)=(2^(m+5)−wIdx(x, y))>>(m+3). m can represent aprecision bit number (e.g., 3 or 6) of the cosine table (e.g., Table 2)that is used to calculate the weighting index.

In an embodiment, the weighting index wIdx(x, y) to the weighting valueweight(x, y) conversion can be derived according to Eq. 13 or Eq. 14.

weight(x,y)=Clip3(0,8,(idx2wOffset−wIdx(x,y))>>idx2wShiftBit)  (Eq. 13)

weight(x,y)=Clip3(0,8,(idx2wOffset+wIdx(x,y))>>idx2wShiftBit)  (Eq. 14)

In Eq. 13 and Eq. 14, a clip function Clip3( ) is used to limit theweighting value weight(x, y) within a predefined range, such as [0, 8].In an example, the offset value idx2wOffset is a linear function of theright shift operand idx2wShiftBit, as shown in Eq. 15.

idx2wOffset=1<<(idx2wShiftBit+2)  (Eq. 15)

The right shift operand idx2wShiftBit can be the precision bit number(e.g., 3, 6, or 9) of the cosine table (e.g., Table 2) that is used tocalculate the weighting index and/or a calculated distance value (e.g.,the weighting index).

In an embodiment, the weighting index can have a sign conversionaccording to a partition index partIdx, as shown in Eq. 16.

wIdxFlip(x,y)=partIdx?−wIdx(x,y):wIdx(x,y)  (Eq. 16)

Accordingly, the weighting value can be derived according to Eq. 17 orEq. 18.

weight(x,y)=Clip3(0,8,(idx2wOffset−wIdxFlip(x,y))>>idx2wShiftBit)  (Eq.17)

weight(x,y)=Clip3(0,8,(idx2wOffset+wIdxFlip(x,y))>>idx2wShiftBit)  (Eq.18)

In an example, the partition index partIdx can be set according to theweighting index of the left-bottom corner sample of the current block.In another example, the partition index partIdx can be set according tothe angle index angleIdx in Eq. 19, where T₁ and T₂ are two thresholds.In one embodiment, T₁=10 and T₂=20.

partIdx=(angleIdx≥T₁&&angleIdx≤T₂)?0:1  (Eq. 19)

In an embodiment, the partition index partIdx can be used as adefinition of a partition for different angles. The weighting value canbe derived according to Eq. 20 and Eq. 21.

wIdxL=(1<<(idx2wShiftBit+2))+(partIdx?wIdx:−wIdx)  (Eq. 20)

weight=Clip3(0,8,(wIdxL+(1<<(idx2wShiftBit−1)))>>idx2wShiftBit)  (Eq.21)

In an embodiment, the weighting value can be derived according to Eq. 22and Eq. 23.

wIdxL=(1<<(idx2wShiftBit+2))+wIdx  (Eq. 22)

weight=Clip3(0,8,(wIdxL+(1<<(idx2wShiftBit−1)))>>idx2wShiftBit)  (Eq.23)

Then, the final blending mask of the sample of the current block can beflipped according to the condition of the angle index angleIdx, which isdescribed in Eq. 19.

According to aspects of the disclosure, the weighting index wIdx(x, y)to the weighting value weight(x, y) conversion can be derived based on apiecewise constant function. The piecewise constant function can includean initial value and a plurality of uni-step functions. Among the rangeof weight factor values, the initial value can be one of a minimumweight factor value and a maximum weighting factor value. Further, anumber of the plurality of unit-step functions can be equal to a totalnumber of the weighting factor values minus 1.

In an embodiment, the weight value weight(x, y) can be derived from apredefined initial value smallestWeight and four unit-step functions, asshown in Eq. 24.

weight(x,y)=smallestWeight+Σ_(i=0) ³ω_(i)(v)  (Eq. 24)

where v is the weighting index and ω_(i)(v) can be derived according toEq. 25 or Eq. 26.

$\begin{matrix}{{\omega_{i}(v)} = \left\{ \begin{matrix}1 & {{{{if}\mspace{14mu} v} \geq c_{i}},} \\0 & {otherwise}\end{matrix} \right.} & \left( {{Eq}.\mspace{11mu} 25} \right) \\{{\omega_{i}(v)} = \left\{ \begin{matrix}1 & {{{{if}\mspace{14mu} v} \geq p_{i}},} \\0 & {otherwise}\end{matrix} \right.} & \left( {{Eq}.\mspace{11mu} 26} \right)\end{matrix}$

Table 4 shows an exemplary look-up table for mapping the weighting indexto the weighting value.

TABLE 4 idx 0 1 2 3 4 5 6 7 8 9 10 11 12 13 GeoFilter[idx] 4 4 4 4 5 5 55 5 5 5 6 6 6 idx 14 15 16 17 18 19 20 21 22 23 24 25 26 GeoFilter[idx]6 6 6 6 7 7 7 7 7 7 7 8 8

If using Eq. 24 and Eq. 25 to represent the Table 4, the initial valuesmallestWeight=4, and the threshold weighting indices C₀-C₃ can be 4,11, 18, and 25, respectively.

If using Eq. 24 and Eq. 26 to represent the Table 4, the initial valuesmallestWeight=4, and the threshold weighting indices P₀-P₃ can be 3,10, 17, and 24, respectively.

Table 5 shows another exemplary look-up table for mapping the weightingindex to the weighting value.

TABLE 5 idx 0 1 2 3 4 5 6 7 8 9 10 11 12 13 GeoFilter[idx] 4 4 4 5 5 5 55 5 5 6 6 6 6 idx 14 15 16 17 18 19 20 21 22 23 24 25 26 GeoFilter[idx]6 6 6 7 7 7 7 7 7 7 7 7 8

If using Eq. 24 and Eq. 25 to represent the Table 5, the initial valuesmallestWeight=4, and the threshold weighting indices C₀-C₃ can be 3,10, 17, and 26, respectively.

If using Eq. 24 and Eq. 26 to represent the Table 5, the initial valuesmallestWeight=4, and the threshold weighting indices P₀-P₃ can be 2, 9,16, and 25, respectively.

In an embodiment, the weight value weight(x, y) can be derived from apredefined initial value largestWeight and four unit-step functions, asshown in Eq. 27.

weight(x,y)=largestWeight−Σ_(i=0) ³ω_(i)(v)  (Eq. 27)

where ω_(i)(v) can be derived according to Eq. 28 or Eq. 29.

$\begin{matrix}{{\omega_{i}(v)} = \left\{ \begin{matrix}1 & {{{{if}\mspace{14mu} v} \leq c_{i}},} \\0 & {otherwise}\end{matrix} \right.} & \left( {{Eq}.\mspace{11mu} 28} \right) \\{{\omega_{i}(v)} = \left\{ \begin{matrix}1 & {{{{if}\mspace{14mu} v} < p_{i}},} \\0 & {otherwise}\end{matrix} \right.} & \left( {{Eq}.\mspace{11mu} 29} \right)\end{matrix}$

If using Eq. 27 and Eq. 28 to represent the Table 4, the initial valuelargestWeight=8, and the threshold weighting indices C₀-C₃ can be 3, 10,17, and 24, respectively.

If using Eq. 27 and Eq. 29 to represent the Table 4, the initial valuelargestWeight=8, and the threshold weighting indices P₀-P₃ can be 4, 11,18, and 25, respectively.

If using Eq. 27 and Eq. 28 to represent the Table 5, the initial valuelargestWeight=8, and the threshold weighting indices C₀-C₃ can be 2, 9,16, and 25, respectively.

If using Eq. 27 and Eq. 29 to represent the Table 5, the initial valuelargestWeight=8, and the threshold weighting indices P₀-P₃ can be 3, 10,17, and 26, respectively.

It is noted that the relational operators (≥) and (>) yield 1 if thecorresponding relation is true and 0 if the corresponding relation isfalse, as defined in C and C++ for example.

VII. Flowchart

FIG. 12 shows a flow chart outlining an exemplary process (1200)according to an embodiment of the disclosure. In various embodiments,the process (1200) is executed by processing circuitry, such as theprocessing circuitry in the terminal devices (210), (220), (230) and(240), the processing circuitry that performs functions of the videoencoder (303), the processing circuitry that performs functions of thevideo decoder (310), the processing circuitry that performs functions ofthe video decoder (410), the processing circuitry that performsfunctions of the intra prediction module (452), the processing circuitrythat performs functions of the video encoder (503), the processingcircuitry that performs functions of the predictor (535), the processingcircuitry that performs functions of the intra encoder (622), theprocessing circuitry that performs functions of the intra decoder (772),and the like. In some embodiments, the process (1200) is implemented insoftware instructions, thus when the processing circuitry executes thesoftware instructions, the processing circuitry performs the process(1200).

The process (1200) may generally start at step (S1210), where theprocess (1200) decodes prediction information of a current block of acurrent picture in a coded bitstream. The prediction informationindicates a geometric partitioning mode (GPM) for the current block. Thecurrent block is partitioned into two partitions in the GPM mode. Eachof the partitions is associated with a respective predictor. Then, theprocess (1200) proceeds to step (S1220).

At step (S1220), the process (1200) determines a weighting index for asample of the current block based on a position of the sample. Then, theprocess (1200) proceeds to step (S1230).

At step (S1230), the process (1200) calculates a weighting factor basedon the weighting index of the sample according to an equation thatconverts the weighting index to the weighting factor. Then, the process(1200) proceeds to step (S1240).

At step (S1240), the process (1200) reconstructs the sample based on theweighting factor and the predictor corresponding to the sample. Afterreconstructing the sample, the process (1200) terminates.

In an embodiment, a right shift operation is performed on a sum of theweighting index and an offset value. A result of the right shiftoperation is clipped to be within a predefined range.

In an embodiment, the offset value is based on a number of bits shiftedby the right shift operation, and the number of bits shifted by theright shift operation is based on at least one of the weighting indexand a size of a cosine table used to calculate the weighting index.

In an embodiment, an angle index and a distance index that define asplit boundary between the partitions of the current block aredetermined based on the GPM. The weighting index for the sample isdetermined based on the position of the sample, the angle index, and thedistance index.

In an embodiment, a partition index is determined based on the angleindex. The weighting factor is calculated based on the partition index.

In an embodiment, the equation is

weight=Clip3(0,8,(wIdxL+(1<<(idx2wShiftBit−1)))>>idx2wShiftBit),

wherein

wIdxL=(1<<(idx2wShiftBit+2))+(partIdx?wIdx:−wIdx),

where idx2wShiftBit indicates the number of bits shifted by the rightshift operation, partIdx is the partition index, and wIdx is theweighting index.

In an embodiment, the equation is a piecewise constant function thatincludes an initial value and a plurality of unit-step functions. Theinitial value is one of a minimum weighting factor value or a maximumweighting factor value, and a number of the plurality of unit-stepfunctions is equal to a total number of different weighting factorvalues minus one.

VIII. Computer System

The techniques described above, can be implemented as computer softwareusing computer-readable instructions and physically stored in one ormore computer-readable media. For example, FIG. 13 shows a computersystem (1300) suitable for implementing certain embodiments of thedisclosed subject matter.

The computer software can be coded using any suitable machine code orcomputer language, that may be subject to assembly, compilation,linking, or like mechanisms to create code comprising instructions thatcan be executed directly, or through interpretation, micro-codeexecution, and the like, by one or more computer central processingunits (CPUs), Graphics Processing Units (GPUs), and the like.

The instructions can be executed on various types of computers orcomponents thereof, including, for example, personal computers, tabletcomputers, servers, smartphones, gaming devices, internet of thingsdevices, and the like.

The components shown in FIG. 13 for computer system (1300) are exemplaryin nature and are not intended to suggest any limitation as to the scopeof use or functionality of the computer software implementingembodiments of the present disclosure. Neither should the configurationof components be interpreted as having any dependency or requirementrelating to any one or combination of components illustrated in theexemplary embodiment of a computer system (1300).

Computer system (1300) may include certain human interface inputdevices. Such a human interface input device may be responsive to inputby one or more human users through, for example, tactile input (such as:keystrokes, swipes, data glove movements), audio input (such as: voice,clapping), visual input (such as: gestures), olfactory input (notdepicted). The human interface devices can also be used to capturecertain media not necessarily directly related to conscious input by ahuman, such as audio (such as: speech, music, ambient sound), images(such as: scanned images, photographic images obtain from a still imagecamera), video (such as two-dimensional video, three-dimensional videoincluding stereoscopic video).

Input human interface devices may include one or more of (only one ofeach depicted): keyboard (1301), mouse (1302), trackpad (1303), touchscreen (1310), data-glove (not shown), joystick (1305), microphone(1306), scanner (1307), camera (1308).

Computer system (1300) may also include certain human interface outputdevices. Such human interface output devices may be stimulating thesenses of one or more human users through, for example, tactile output,sound, light, and smell/taste. Such human interface output devices mayinclude tactile output devices (for example tactile feedback by thetouch-screen (1310), data-glove (not shown), or joystick (1305), butthere can also be tactile feedback devices that do not serve as inputdevices), audio output devices (such as: speakers (1309), headphones(not depicted)), visual output devices (such as screens (1310) toinclude CRT screens, LCD screens, plasma screens, OLED screens, eachwith or without touch-screen input capability, each with or withouttactile feedback capability—some of which may be capable to output twodimensional visual output or more than three dimensional output throughmeans such as stereographic output; virtual-reality glasses (notdepicted), holographic displays and smoke tanks (not depicted)), andprinters (not depicted). These visual output devices (such as screens(1310)) can be connected to a system bus (1348) through a graphicsadapter (1350).

Computer system (1300) can also include human accessible storage devicesand their associated media such as optical media including CD/DVD ROM/RW(1320) with CD/DVD or the like media (1321), thumb-drive (1322),removable hard drive or solid state drive (1323), legacy magnetic mediasuch as tape and floppy disc (not depicted), specialized ROM/ASIC/PLDbased devices such as security dongles (not depicted), and the like.

Those skilled in the art should also understand that term “computerreadable media” as used in connection with the presently disclosedsubject matter does not encompass transmission media, carrier waves, orother transitory signals.

Computer system (1300) can also include a network interface (1354) toone or more communication networks (1355). The one or more communicationnetworks (1355) can for example be wireless, wireline, optical. The oneor more communication networks (1355) can further be local, wide-area,metropolitan, vehicular and industrial, real-time, delay-tolerant, andso on. Examples of the one or more communication networks (1355) includelocal area networks such as Ethernet, wireless LANs, cellular networksto include GSM, 3G, 4G, 5G, LTE and the like, TV wireline or wirelesswide area digital networks to include cable TV, satellite TV, andterrestrial broadcast TV, vehicular and industrial to include CANBus,and so forth. Certain networks commonly require external networkinterface adapters that attached to certain general purpose data portsor peripheral buses (1349) (such as, for example USB ports of thecomputer system (1300)); others are commonly integrated into the core ofthe computer system (1300) by attachment to a system bus as describedbelow (for example Ethernet interface into a PC computer system orcellular network interface into a smartphone computer system). Using anyof these networks, computer system (1300) can communicate with otherentities. Such communication can be uni-directional, receive only (forexample, broadcast TV), uni-directional send-only (for example CANbus tocertain CANbus devices), or bi-directional, for example to othercomputer systems using local or wide area digital networks. Certainprotocols and protocol stacks can be used on each of those networks andnetwork interfaces as described above.

Aforementioned human interface devices, human-accessible storagedevices, and network interfaces can be attached to a core (1340) of thecomputer system (1300).

The core (1340) can include one or more Central Processing Units (CPU)(1341), Graphics Processing Units (GPU) (1342), specialized programmableprocessing units in the form of Field Programmable Gate Areas (FPGA)(1343), hardware accelerators for certain tasks (1344), and so forth.These devices, along with Read-only memory (ROM) (1345), Random-accessmemory (1346), internal mass storage such as internal non-useraccessible hard drives, SSDs, and the like (1347), may be connectedthrough the system bus (1348). In some computer systems, the system bus(1348) can be accessible in the form of one or more physical plugs toenable extensions by additional CPUs, GPU, and the like. The peripheraldevices can be attached either directly to the core's system bus (1348),or through a peripheral bus (1349). Architectures for a peripheral businclude PCI, USB, and the like.

CPUs (1341), GPUs (1342), FPGAs (1343), and accelerators (1344) canexecute certain instructions that, in combination, can make up theaforementioned computer code. That computer code can be stored in ROM(1345) or RAM (1346). Transitional data can be also be stored in RAM(1346), whereas permanent data can be stored for example, in theinternal mass storage (1347). Fast storage and retrieve to any of thememory devices can be enabled through the use of cache memory, that canbe closely associated with one or more CPU (1341), GPU (1342), massstorage (1347), ROM (1345), RAM (1346), and the like.

The computer readable media can have computer code thereon forperforming various computer-implemented operations. The media andcomputer code can be those specially designed and constructed for thepurposes of the present disclosure, or they can be of the kind wellknown and available to those having skill in the computer software arts.

As an example and not by way of limitation, the computer system havingarchitecture (1300), and specifically the core (1340) can providefunctionality as a result of processor(s) (including CPUs, GPUs, FPGA,accelerators, and the like) executing software embodied in one or moretangible, computer-readable media. Such computer-readable media can bemedia associated with user-accessible mass storage as introduced above,as well as certain storage of the core (1340) that are of non-transitorynature, such as core-internal mass storage (1347) or ROM (1345). Thesoftware implementing various embodiments of the present disclosure canbe stored in such devices and executed by core (1340). Acomputer-readable medium can include one or more memory devices orchips, according to particular needs. The software can cause the core(1340) and specifically the processors therein (including CPU, GPU,FPGA, and the like) to execute particular processes or particular partsof particular processes described herein, including defining datastructures stored in RAM (1346) and modifying such data structuresaccording to the processes defined by the software. In addition or as analternative, the computer system can provide functionality as a resultof logic hardwired or otherwise embodied in a circuit (for example:accelerator (1344)), which can operate in place of or together withsoftware to execute particular processes or particular parts ofparticular processes described herein. Reference to software canencompass logic, and vice versa, where appropriate. Reference to acomputer-readable media can encompass a circuit (such as an integratedcircuit (IC)) storing software for execution, a circuit embodying logicfor execution, or both, where appropriate. The present disclosureencompasses any suitable combination of hardware and software.

While this disclosure has described several exemplary embodiments, thereare alterations, permutations, and various substitute equivalents, whichfall within the scope of the disclosure. It will thus be appreciatedthat those skilled in the art will be able to devise numerous systemsand methods which, although not explicitly shown or described herein,embody the principles of the disclosure and are thus within the spiritand scope thereof.

APPENDIX A: ACRONYMS

-   AMT: Adaptive Multiple Transform-   AMVP: Advanced Motion Vector Prediction-   ASIC: Application-Specific Integrated Circuit-   ATMVP: Alternative/Advanced Temporal Motion Vector Prediction-   BDOF: Bi-directional Optical Flow-   BDPCM (or RDPCM): Residual Difference Pulse Coded Modulation-   BIO: Bi-directional Optical Flow-   BMS: Benchmark Set-   BT: Binary Tree-   BV: Block Vector-   CANBus: Controller Area Network Bus-   CB: Coding Block-   CBF: Coded Block Flag-   CCLM: Cross-Component Linear Mode/Model-   CD: Compact Disc-   CPR: Current Picture Referencing-   CPU: Central Processing Unit-   CRT: Cathode Ray Tube-   CTB: Coding Tree Block-   CTU: Coding Tree Unit-   CU: Coding Unit-   DM: Derived Mode-   DPB: Decoder Picture Buffer-   DVD: Digital Video Disc-   EMT: Enhanced Multiple Transform-   FPGA: Field Programmable Gate Areas-   GOP: Group of Picture-   GPU: Graphics Processing Unit-   GSM: Global System for Mobile communications-   HDR: High Dynamic Range-   HEVC: High Efficiency Video Coding-   HRD: Hypothetical Reference Decoder-   IBC: Intra Block Copy-   IC: Integrated Circuit-   IDT: Identify Transform-   ISP: Intra Sub-Partitions-   JEM: Joint Exploration Model-   JVET: Joint Video Exploration Team-   LAN: Local Area Network-   LCD: Liquid-Crystal Display-   LFNST: Low Frequency Non-Separable Transform, or Low Frequency    Non-Separable Secondary Transform-   LTE: Long-Term Evolution-   L_CCLM: Left-Cross-Component Linear Mode/Model-   LT_CCLM: Left and Top Cross-Component Linear Mode/Model-   MIP: Matrix based Intra Prediction-   MPM: Most Probable Mode-   MRLP (or MRL): Multiple Reference Line Prediction-   MTS: Multiple Transform Selection-   MV: Motion Vector-   NSST: Non-Separable Secondary Transform-   OLED: Organic Light-Emitting Diode-   PBs: Prediction Blocks-   PCI: Peripheral Component Interconnect-   PDPC: Position Dependent Prediction Combination-   PLD: Programmable Logic Device-   PPR: Parallel-Processable Region-   PPS: Picture Parameter Set-   PU: Prediction Unit-   QT: Quad-Tree-   RAM: Random Access Memory-   ROM: Read-Only Memory-   RST: Reduced-Size Transform-   SBT: Sub-block Transform-   SCC: Screen Content Coding-   SCIPU: Small Chroma Intra Prediction Unit-   SDR: Standard Dynamic Range-   SEI: Supplementary Enhancement Information-   SNR: Signal Noise Ratio-   SPS: Sequence Parameter Set-   SSD: Solid-state Drive-   SVT: Spatially Varying Transform-   TSM: Transform Skip Mode-   TT: Ternary Tree-   TU: Transform Unit-   T_CCLM: Top Cross-Component Linear Mode/Model-   USB: Universal Serial Bus-   VPDU: Visual Process Data Unit-   VPS: Video Parameter Set-   VUI: Video Usability Information-   VVC: Versatile Video Coding-   WAIP: Wide-Angle Intra Prediction

What is claimed is:
 1. A method for video coding in an encoder,comprising: partitioning a current block of a current picture based on ageometric partitioning mode (GPM), the current block being partitionedinto two partitions in the GPM mode, and each of the partitions beingassociated with a respective predictor; determining a weighting indexfor a sample of the current block based on a position of the sample;calculating a weighting factor based on the weighting index of thesample according to an equation that converts the weighting index to theweighting factor; and encoding the sample based on the weighting factorand the predictor corresponding to the sample.
 2. The method of claim 1,wherein the calculating comprises: performing a right shift operation ona sum of the weighting index and an offset value; and clipping a resultof the right shift operation to be within a predefined range.
 3. Themethod of claim 2, wherein the offset value is based on a number of bitsshifted by the right shift operation, and the number of bits shifted bythe right shift operation is based on at least one of the weightingindex and a size of a cosine table used to calculate the weightingindex.
 4. The method of claim 1, wherein the determining the weightingindex comprises: determining an angle index and a distance index thatdefine a split boundary between the partitions of the current blockbased on the GPM; and determining the weighting index for the samplebased on the position of the sample, the angle index, and the distanceindex.
 5. The method of claim 4, wherein the calculating comprises:determining a partition index based on the angle index; and calculatingthe weighting factor based on the partition index.
 6. The method ofclaim 5, wherein the equation isweight=Clip3(0,8,(wIdxL+(1<<(idx2wShiftBit−1)))>>idx2wShiftBit), whereinwIdxL=(1<<(idx2wShiftBit+2))+(partIdx?wIdx:−wIdx), where idx2wShiftBitindicates a number of bits shifted by a right shift operation, weight isthe weighting factor, partIdx is the partition index, wIdx is theweighting index, and Clip3( ) is a clipping function.
 7. The method ofclaim 1, wherein the equation is a piecewise constant function thatincludes an initial value and a plurality of unit-step functions.
 8. Themethod of claim 7, wherein the initial value is one of a minimumweighting factor value or a maximum weighting factor value, and a numberof the plurality of unit-step functions is equal to a total number ofdifferent weighting factor values minus one.
 9. An apparatus, comprisingprocessing circuitry configured to: partition a current block of acurrent picture based on a geometric partitioning mode (GPM), thecurrent block being partitioned into two partitions in the GPM mode, andeach of the partitions being associated with a respective predictor;determine a weighting index for a sample of the current block based on aposition of the sample; calculate a weighting factor based on theweighting index of the sample according to an equation that converts theweighting index to the weighting factor; and encode the sample based onthe weighting factor and the predictor corresponding to the sample. 10.The apparatus of claim 9, wherein the processing circuitry is furtherconfigured to: perform a right shift operation on a sum of the weightingindex and an offset value; and clip a result of the right shiftoperation to be within a predefined range.
 11. The apparatus of claim10, wherein the offset value is based on a number of bits shifted by theright shift operation, and the number of bits shifted by the right shiftoperation is based on at least one of the weighting index and a size ofa cosine table used to calculate the weighting index.
 12. The apparatusof claim 9, wherein the processing circuitry is further configured to:determine an angle index and a distance index that define a splitboundary between the partitions of the current block based on the GPM;and determine the weighting index for the sample based on the positionof the sample, the angle index, and the distance index.
 13. Theapparatus of claim 12, wherein the processing circuitry is furtherconfigured to: determine a partition index based on the angle index; andcalculate the weighting factor based on the partition index.
 14. Theapparatus of claim 13, wherein the equation isweight=Clip3(0,8,(wIdxL+(1<<(idx2wShiftBit−1)))>>idx2wShiftBit), whereinwIdxL=(1<<(idx2wShiftBit+2))+(partIdx?wIdx:−wIdx), where idx2wShiftBitindicates a number of bits shifted by a right shift operation, weight isthe weighting factor, partIdx is the partition index, wIdx is theweighting index, and Clip3( ) is a clip function.
 15. The apparatus ofclaim 9, wherein the equation is a piecewise constant function thatincludes an initial value and a plurality of unit-step functions. 16.The apparatus of claim 15, wherein the initial value is one of a minimumweighting factor value or a maximum weighting factor value, and a numberof the plurality of unit-step functions is equal to a total number ofdifferent weighting factor values minus one.
 17. A non-transitorycomputer-readable storage medium storing a program executable by atleast one processor to perform: partitioning a current block of acurrent picture based on a geometric partitioning mode (GPM), thecurrent block being partitioned into two partitions in the GPM mode, andeach of the partitions being associated with a respective predictor;determining a weighting index for a sample of the current block based ona position of the sample; calculating a weighting factor based on theweighting index of the sample according to an equation that converts theweighting index to the weighting factor; and encoding the sample basedon the weighting factor and the predictor corresponding to the sample.18. The non-transitory computer-readable storage medium of claim 17,wherein the calculating comprises: performing a right shift operation ona sum of the weighting index and an offset value; and clipping a resultof the right shift operation to be within a predefined range.
 19. Thenon-transitory computer-readable storage medium of claim 18, wherein theoffset value is based on a number of bits shifted by the right shiftoperation, and the number of bits shifted by the right shift operationis based on at least one of the weighting index and a size of a cosinetable used to calculate the weighting index.
 20. The non-transitorycomputer-readable storage medium of claim 17, wherein the determiningthe weighting index comprises: determining an angle index and a distanceindex that define a split boundary between the partitions of the currentblock based on the GPM; and determining the weighting index for thesample based on the position of the sample, the angle index, and thedistance index.